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Google Translation Center is a straightforward and very clever way to gather a large corpus of parallel texts to train its machine translation systems.

If Google releases an API for the translation management system, it could establish a de facto standard for integrated machine translation and translation memory, creating a language platform around which projects like Der Mundo can build specialized applications and collect more training data.

On the other hand, GTC could be bad news for translation service bureaus — especially those that use proprietary translation management systems as a way to hold customers and translators hostage.

For freelancers, GTC could be very good news; they could work directly with clients and have access to high quality productivity tools. Overall this is a welcome move that will force service providers to focus on quality, while Google, which is competent at software, can focus on building tools.

That strategy would also eliminate a potential conflict of interest

translation professionals are understandably wary of contributing to something that could put them out of work

as well as avoid channel conflicts with partners who will be their best advocates in selling to various clients

my guess is Google will make this a free tool for the translation industry to use, and it will figure the money part out later. It can afford to be patient

I remain convinced that a multilingual web will be a reality in a short time, and that a menagerie of tools and services will emerge over the next few years — some geared toward helping translators, some toward building translation communities, and others that make publishing multilingual sites and blogs easy and intuitive.

the web will begin translating itself, and within a short time

The Translation Centre helps Google to reach out to non-professional translators (the ‘crowd'),

According to John Patrick, IBM's vice president for Internet strategies, "the next big thing will be grid computing

It is a form of distributed computing whereby a "super and virtual computer" is composed of a cluster of networked, loosely coupled computers, acting in concert to perform very large tasks.

It can be small -- confined to a network of computer workstations within a corporation, for example -- or it can be a large, public collaboration across many companies or networks.

"Distributed" or "grid" computing in general is a special type of parallel computing[citation needed] that relies on complete computers

connected to a network

by a conventional network interface, such as Ethernet.

The primary advantage of distributed computing is that each node can be purchased as commodity hardware, which when combined can produce similar computing resources to a multiprocessor supercomputer, but at lower cost.

One feature of distributed grids is that they can be formed from computing resources belonging to multiple individuals or organizations (known as multiple administrative domains). This can facilitate commercial transactions, as in utility computing, or make it easier to assemble volunteer computing networks.

Grids offer a way to solve Grand Challenge problems such as protein folding, financial modeling, earthquake simulation, and climate/weather modeling.

The European Union has been a major proponent of Grid computing.

According to John Patrick, formerly IBM's vice president for Internet strategies, "the next big thing will be grid computing." [1]

back-office data processing in support of e-commerce and Web services.

European DataGrid (EDG) and is arguably the largest computing grid on the planet

along with the LHC Computing Grid [5] (LCG), has been developed to support the experiments using the CERN Large Hadron Collider. The LCG project is driven by CERN's need to handle huge amounts of data, where storage rates of several gigabytes per second (10 petabytes per year) are required.